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Balakrishna Eppakayala (17 results)
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Mining Association Rules from Incremental Data set
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204980947 ISBN 13: 9786204980942
Condition: New.
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Modified Frequent Pattern Tree for Mining Negative Association Rules
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Condition: New.
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Minería de reglas de asociación a partir de un conjunto de datos incrementales
Language: Spanish
Published by Ediciones Nuestro Conocimiento, 2022
ISBN 10: 6205009765 ISBN 13: 9786205009765
Condition: New.
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Modified Frequent Pattern Tree for Mining Negative Association Rules | A Data Mining Techniques for Market Basket Analysis
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Taschenbuch. Condition: Neu. Modified Frequent Pattern Tree for Mining Negative Association Rules | A Data Mining Techniques for Market Basket Analysis | Eppakayala Balakrishna (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204979540 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Extraction de règles d\ association à partir d\ un ensemble de données incrémentielles
Language: French
Published by Editions Notre Savoir, 2022
ISBN 10: 6205009676 ISBN 13: 9786205009673
Condition: New.
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Regras da Associação Mineira do Conjunto de Dados Incrementais
Language: Portuguese
Published by Edições Nosso Conhecimento, 2022
ISBN 10: 6205009692 ISBN 13: 9786205009697
Condition: New.
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Mining Association Rules from Incremental Data set
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204980947 ISBN 13: 9786204980942
Condition: New. Print on Demand.
-
Mining Association Rules from Incremental Data set
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204980947 ISBN 13: 9786204980942
Condition: New. PRINT ON DEMAND.
-
Modified Frequent Pattern Tree for Mining Negative Association Rules
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Condition: New. Print on Demand.
-
Modified Frequent Pattern Tree for Mining Negative Association Rules
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2022, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mining of Negative Association Rule is helpful to discover the competent items i.e., one item can be substituted for another items in a database. In decision making, we generally use many advantage factors, and also consider some disadvantage factors, for the intention of less-risk (more-profit). It is necessary to focus on Negative Association Rule mining, because in the super market data analysis, Negative Association Rule Mining identifies whatever the items which are not buying together and also whatever the items which may be used as replacing (substituted or alternative) items for other items. Such kind of analysis is possible through Negative Association Rule Mining. Negative rules specify that the relationship between the present and absent item-sets. Negative Association Rule mining is also important because such types of rules should be considered in decision making for applications include product placement and investment analysis. 124 pp. Englisch.
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Mining Association Rules from Incremental Data set
Language: English
Published by LAP Lambert Academic Publishing, 2022
ISBN 10: 6204980947 ISBN 13: 9786204980942
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Association Rule Mining (ARM) in data mining provides quality association rules based on measures such as support and confidence. These rules are interpreted by domain experts for making well-informed decisions. However, there is an issue with ARM when the .
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Modified Frequent Pattern Tree for Mining Negative Association Rules
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Condition: New. PRINT ON DEMAND.
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Modified Frequent Pattern Tree for Mining Negative Association Rules
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Balakrishna EppakayalaDr. Eppakayala Balakrishna completed M.Tech and Ph.D in CSE from JNTU University, Hyderabad. He is working as an Associate Professor in the department of CSE, Vaagdevi College of Engineering.Mining of Negati.
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Modified Frequent Pattern Tree for Mining Negative Association Rules
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2022, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mining of Negative Association Rule is helpful to discover the competent items i.e., one item can be substituted for another items in a database. In decision making, we generally use many advantage factors, and also consider some disadvantage factors, for the intention of less-risk (more-profit). It is necessary to focus on Negative Association Rule mining, because in the super market data analysis, Negative Association Rule Mining identifies whatever the items which are not buying together and also whatever the items which may be used as replacing (substituted or alternative) items for other items. Such kind of analysis is possible through Negative Association Rule Mining. Negative rules specify that the relationship between the present and absent item-sets. Negative Association Rule mining is also important because such types of rules should be considered in decision making for applications include product placement and investment analysis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch.
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Modified Frequent Pattern Tree for Mining Negative Association Rules : A Data Mining Techniques for Market Basket Analysis
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 620497954X ISBN 13: 9786204979540
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mining of Negative Association Rule is helpful to discover the competent items i.e., one item can be substituted for another items in a database. In decision making, we generally use many advantage factors, and also consider some disadvantage factors, for the intention of less-risk (more-profit). It is necessary to focus on Negative Association Rule mining, because in the super market data analysis, Negative Association Rule Mining identifies whatever the items which are not buying together and also whatever the items which may be used as replacing (substituted or alternative) items for other items. Such kind of analysis is possible through Negative Association Rule Mining. Negative rules specify that the relationship between the present and absent item-sets. Negative Association Rule mining is also important because such types of rules should be considered in decision making for applications include product placement and investment analysis.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nedendla SatyavathiDr.N.Satyavathi lavora come capo del dipartimento CSE in una prestigiosa istituzione. Ha 17 anni di esperienza nell insegnamento. Ha pubblicato diversi articoli di ricerca in varie riviste Scopus e conferenze inter.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nedendla SatyavathiDr. N. Satyavathi arbeitet als Leiterin der Abteilung CSE in einer renommierten Einrichtung. Sie hat 17 Jahre Erfahrung in der Lehre. Veroeffentlichte verschiedene Forschungsarbeiten in verschiedenen Scopus-Zeitschr.
